Seismic data are typically gathered using an array of detectors. In the case of marine data, hydrophones measure pressure fluctuations in the water caused by incoming seismic waves. Geophones measure vector quantities such as displacement, velocity or acceleration. In the case of marine data, a plurality of cables or streamers, which are spaced apart typically by about 100 meters, are towed behind a boat. Each cable has detectors spaced along the cable at intervals. In the case of land data, a geophone array is laid out on the ground with the geophones in an approximate grid formation. The detector array detects seismic signals from reverberations of a signal from a seismic source, such as an airgun for marine data. In ocean bottom (OBC or OBS) acquisition, a detector array is fixed on the seabed and the source may be an airgun mounted on a boat.
In seismic data processing, the data received by a receiver and then recorded are collectively called a trace. The collection of traces are stored for further processing to gain information about the earth's subsurface. Such information is commonly interpreted to detect the possible presence of hydrocarbons, or to monitor changes in hydrocarbon bearing rocks. The traces are initially recorded as shot gathers, where a plurality of traces, each from a different receiver, which are all data from a single shot. The distance between a seismic source and a receiver for a particular trace is known as the offset and the midpoint is a point midway between the source and receiver position, and represents the point from which the seismic energy is reflected if the reflectors are perfect flat reflectors. In a shot gather the traces are arranged in order of increasing offset. The traces can be sorted to form, for example, common receiver gathers or common midpoint gathers, as is appropriate for the particular processing technique being applied.
Seismic data in general contains coherent noise signals, along with seismic reflection signals. These noise signals, hereafter referred to as the noise, interfere with the interpretation of the seismic signals, and degrade the quality of the subsurface images that can be obtained by further processing. It is therefore desirable to suppress the noise that is present in the recorded data before processing it for imaging.
In land seismic, source generated noise like ground roll and airwaves are the dominant noise types, and can lead to severe degradation in data quality. In marine seismic, energy propagating as waves trapped in the water column and near surface layers is a significant source, as well as swell noise and bulge wave noise which result from waves propagating along the streamers of receiver devices. Other sources of coherent noise in marine seismic include passing vessels, other vessels acquiring seismic data in the vicinity, or any drilling activity close to the survey area. Swell noise in particular increases rapidly with heavy weather conditions. Furthermore, recent developments in acquisition have lead to an increase in swell noise. For instance, some recent developments in acquisition have employed streamer steering techniques to control the drift of streamers to maintain the streamers as close as possible to a straight line extending behind the boat and to maintain the plurality of streamers as close as possible to being parallel to each other. However, such streamer steering techniques result in an increase in swell noise.
During a marine towed streamer seismic survey, up to 45% of the production time may be spent turning the boat between lines. Data is usually not shot during turning or is rendered useless or of extremely low quality by high levels of streamer noise, which is caused by cross flow of the water. If quality data could be obtained from data shot during turns by processing techniques capable of removing this noise, then production efficiency could be greatly increased.
In seismic data processing, a common processing step is velocity (or dip) filtering, where wave field components faster than a given apparent velocity c are past, and the rest are rejected.
One method of implementing a velocity filter is as an f-k filter in the frequency-wavenumber domain. The filter is essentially a mask that is multiplied by a 2-D Fourier transform of the data. An example of an f-k filter is shown in FIG. 1. However, f-k filters suffer from edge effects and transients. (See, for example, Lloyd G. Peardon, F K Techniques in Seismic Processing in E. A. Robinson, T. S. Durrani with a Chapter by L. G. Peardon, Geophysical Signal Processing, pp. 388-467 (Prentice Hall Int'l 1986).
Another way of implementing a velocity filter is as a t-x filter, in the time-space domain using a 2D FIR (finite impulse response) filter. However, these also have a relatively slow transition from the pass to the reject regions, due to the finite length of the filter impulse response. As the filter gets larger, edge effects and computational costs can become significant. 2D IIR (infinite impulse response) filters can also be used in the time-space domain, but these have serious stability problems.